Flow cytometer can receive photoelectric signals generated by irradiating cells with laser and graphically present the photoelectric signals for the analysis of the user. Scattered light signals and fluorescence signals of the photoelectric signals can represent physical and chemical properties of the cells, such as the size of the cell, the graininess and the expression of antigen molecules, etc.
FIG. 1 schematically shows an existing flow cytometer, which mainly includes an optical system, a fluid system, a mechanical system, a control and signal processing system, related peripherals and a software system (not shown). The fluid system is mainly used to form a sample stream with the sample to be analyzed and enable the flow of the sample stream to be adjustable. The optical system is mainly used to generate laser to irradiate the sample stream to generate forward and side fluorescence signals. The control and signal processing system is mainly used to perform photoelectric conversion and control the cytometer. The software system is mainly used to represent the information about the height, area or the like of particles in visual graphs by setting related photoelectric conversion parameters and pulse identification parameters, for the analysis of the user by a variety of tools.
Representing the information about the height, area or the like of the particles in visual graphs is generally implemented by a routine as shown in FIG. 2. In this routine, the sample stream flows through a flow chamber, and the cells in the stream generate scattered light signals and fluorescence signals after being irradiated by the laser. The photoelectric conversion unit converts these optical signals into electric signals, and performs suitable processing on them. The processed signals are analog signals, which need to be converted into digital signals by AD conversion (analog to digital conversion) and AD acquisition for following data processing. Since the data the user needs is the information about the height, area or the like of the particles, pulse identification needs to be performed on the acquired digital signals in order to identify the effective particles to further calculate the height and area of the particles. Then, the information about the height or the area is transmitted to a computer and translated into graph such as dot plot, histogram or the like by the software system.
FIG. 3 schematically shows an electric signal converted from an optical signal of an existing flow cytometer, which undergoes the photoelectric conversion and circuit processing and is presented in voltage. A typical dot plot is shown in FIG. 4.
The fluorescence signals are excited by irradiating fluorescein with the laser. However, the wavelengths of the generated fluorescence signals are generally not a fixed wavelength as in an ideal state, but distributed in a certain distribution curve. In order to acquire the fluorescence data representing a certain property, the flow cytometer uses bandpass filters to filter out interference signals to ensure that most of the acquired signals are fluorescence signals which can represent the properties of the irradiated subject. FIG. 5 schematically shows the wavelength distribution and the working principle of the bandpass filter. As shown in FIG. 5, based on the currently used laser, fluorescein and bandpass filter, it can not be completely ensured that the signals from a variety of channels will not interfere with each other. In FIG. 5, the interference between two channels exists at A and B, which will lead to deviation of the data of the irradiated subject acquired in corresponding channels. In order to overcome this drawback, a fluorescence compensation method is generally used in the art to eliminate the interference between the channels, such that the data which can truly represent the actual properties of the irradiated subject can be shown in the presented graphs. The fluorescence compensation is generally implemented in the form of a table, where each table cell represents a correction in percentage to the leakage (interference) from a channel A to a channel B.
However, for the fluorescence compensation method by the table, it is needed to acquire the data of the plurality of fluorescence channels using a plurality of tests under a known voltage, and compensation values of the plurality of table cells need to be calculated according to the data of the plurality of channels, which is costly and time-consuming. Furthermore, in clinical practice, the compensation values of the graphs often need to be adjusted and the user usually tries to adjust the compensation values several times until particle clusters are distributed in the dot plot in a “smooth vertical and horizontal” shape, i.e., cell populations are substantially equally positioned in a certain direction. For example, a target dot plot shown in FIG. 6 may be obtained from the data of the dot plot shown in FIG. 4 by compensating the dot plot after a plurality of manual adjustments of the compensation system.
However, the inventors have found that there are some difficulties for the user to implement the graph-based compensation using the existing method. First, after the user determines a direction for compensation, it will take experience for the user to determine which cell of a compensation matrix needs to be adjusted, which can only be accurately determined with very rich experience. Second, when the user performs manual adjustment, a suitable compensation value can generally be obtained after a plurality of cycles of compensation adjustment, graph observation, and reviewing and analysis of statistical results, which is cumbersome, complicated and inaccurate.